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In order to read any of the classic (and important) papers on energy-based neural networks, we need to know the vocabulary and essential concepts from: In today’s associated YouTube video, we illustrate how these different terms – and their respective disciplines – are blended together, using the Salakhutdinov and Hinton (2012) paper as a reference… Continue reading Learning Energy-Based Neural Networks

Socrates is a name that most of us know, even if only tangentially. We’ve probably all heard of the “Socratic method” of teaching. Many of us also know of Pericles, the great Athenian general who lead their armies in their various wars – including those against Sparta. But Aspasia? Not as many of us have… Continue reading Socrates, Pericles, and Aspasia: How A Muse Helped the Genesis of Western Thought

This is the blogpost associated with THIS YOUTUBE: The BEST “Readings” Resources to go with this YouTube are TWO prior blogposts: Also, the prior neurophysiology-oriented YouTube has a LOT of useful content – it’s all on how the neurophysiology that we can use as inspiration has evolved over these past 50 ++ years. So the… Continue reading Neurophysiology-Based AGI Framework in 2024

One of the most important things that we can do, in creating AGI (artificial general intelligence), is to work through the latent variable issues that are foremost in AI and machine learning (ML) research now. We identified these in our July 10, 2023 blogpost on Latent Variables in Neural Networks and Machine Learning. We wrote… Continue reading The AI Salon: AGI and Latent Variables

The most important element in creating an AGI (artificial general intelligence) is that the latent node layer needs to allow a range of neural dynamics. The most important of these dynamics will be the ability for the system to rapidly undergo a state change, from mostly “off” nodes to mostly “on.” Neurophysiologists have observed this… Continue reading The 1D CVM (Cluster Variation Method): Complete Interactive Code (Part 2)

The next era of artificial intelligence (AI), or artificial general intelligence (AGI), will rest on neurophysiology models that emphasize neuronal group dynamics, rather than the behaviors of single neurons. This post addresses three questions that underlie the next-era neurophysiological underpinnings supporting neural networks – the NEXT generation of neural networks modeling: Neurophysiology: Important Early Works… Continue reading Next-Era AGI: Neurophysiology Basis

This briefing is the first step for those considering research and development (R&D) involving CORTECONs (COntent-Retentive, TEmporally-CONnected neural networks), which have been developed by Themesis Principal Alianna J. Maren, Ph.D. We organize this briefing using the five well-known questions for reporting: This briefing accompanies a YouTube presentation, and the link to that presentation will be… Continue reading CORTECONs: Executive / Board / Investor Briefing

Two weeks ago, for the first time, I whipped out my credit card and signed up with Medium.com – all to access just a single article. For years, I’d successfully resisted that siren-call from Medium, keeping my access to the monthly minimum. But this one … was a must-read. A Bit of Backstory For those… Continue reading Your AI Career: Positioning Yourself for Maximal Win

Latent variables are one of the most important concepts in both energy-based neural networks (the restricted Boltzmann machine and everything that descends from it), as well as key natural language processing (NLP) algorithms such as LDA (latent Dirichlet allocation), all forms of transformers, and machine learning methods such as variational inference. The notion of finding… Continue reading Latent Variables in Neural Networks and Machine Learning

A new class of neural networks will use a laterally-connected neuron layer (hidden or “latent” nodes) to enable three new kinds of temporal behavior:  Memory persistence (“Holding that thought”) – neural clusters with variable slow activation degradation, allowing persistent activation after stimulus presentation, Learned temporal associations (“That reminds me …”) – neural clusters with slowly… Continue reading Key Features for a New Class of Neural Networks